Agent skill · redis
redis-search
Redis Search guidance covering FT.CREATE schema design, field type selection (TEXT, TAG, NUMERIC, GEO, GEOSHAPE, VECTOR, JSON path), DIALECT 2 query syntax, FT.SEARCH / FT.AGGREGATE / FT.HYBRID command selection, vector similarity with HNSW or FLAT, hybrid retrieval combining lexical and vector ranking, RAG pipelines, zero-downtime index updates via aliases, and debugging with FT.PROFILE and FT.EXPLAIN. Use when defining a search index on Hash or JSON documents, writing FT.SEARCH queries with filters, sorting, aggregation, or vector KNN, tuning HNSW parameters, building a RAG retrieval pipeline, or troubleshooting slow or empty search results.
What it needs
About 5k tokens when loaded.
What this skill does
Redis Search Single source of guidance for Redis Search — the retrieval surface that spans lexical, numeric, geo, JSON-path, and vector queries. Vector fields are part of the same FT.CREATE machinery as TEXT/TAG/NUMERIC fields, and FT.HYBRID blends lexical and vector ranking in one command, so this skill covers them together. When to apply Creating, modifying, or reviewing a Redis Search index (FT.CREATE, FT.ALTER). Writing or optimizing FT.SEARCH, FT.AGGREGATE, or FT.HYBRID queries. Picking between TEXT, TAG, NUMERIC, GEO, GEOSHAPE, VECTOR, or JSON-path fields. Defining a VECTOR field, choosing HNSW vs FLAT, tuning HNSW parameters. Building a retrieval-augmented generation (RAG) pipeline. Rolling out a new index schema without downtime. Troubleshooting empty results, slow queries, or tokenization issues with FT.EXPLAIN, FT.PROFILE, FT.INFO. 1. Pick the right command Three query commands. Reach for the narrowest one that fits. Command When to use Mental model Minimum Redis --- --- --- --- FT.SEARCH Document retrieval, ranked or sorted. Best default. Returns matching docs directly. 2.0 (module) / 8.0 (built-in) FT.AGGREGATE Faceting, computed fields, custom output shape, analytics. Declarative pipeline: LOAD, APPLY, GROUPBY, REDUCE, SORTBY. 2.0 / 8.0 FT.HYBRID Blend lexical (BM25) with vector similarity, with configurable fusion. Pipeline with explicit SEARCH + VSIM legs and a COMBINE fusion stage. 8.4.0 For Redis < 8.4 the lexical+vector blend is approximated with FT.SEARCH pre-filter + =>[KNN ...]. See references/command-selection.md and references/hybrid-search.md. 2. Schema basics — FT.CREATE FT.CREATE indexes Hash or JSON documents matching a PREFIX. Always set PREFIX. Use DIALECT 2 (the default since Redis 8; required for vector queries). …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills redis/redis-search--a0a546